Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/150282
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Characterizing the environments of supernovae with MUSE |
Autor: | Galbany, Lluís CSIC ORCID ; Pérez Jiménez, Enrique CSIC ORCID ; Moral, V. | Palabras clave: | Supernovae: general Techniques: spectroscopic Methods: statistical H II regions Galaxies: general |
Fecha de publicación: | 2016 | Editor: | Oxford University Press | Citación: | Monthly Notices of the Royal Astronomical Society 455: 4087- 4099 (2016) | Resumen: | We present a statistical analysis of the environments of 11 supernovae (SNe) which occurred in six nearby galaxies (z ≲ 0.016). All galaxies were observed with MUSE, the high spatial resolution integral-field spectrograph mounted to the 8 m VLT UT4. These data enable us to map the full spatial extent of host galaxies up to ~3 effective radii. In this way, not only can one characterize the specific host environment of each SN, one can compare their properties with stellar populations within the full range of other environments within the host. We present a method that consists of selecting all HII regions found within host galaxies from 2D extinction-corrected Hα emission maps. These regions are then characterized in terms of their Hα equivalent widths, star formation rates and oxygen abundances. Identifying HII regions spatially coincident with SN explosion sites, we are thus able to determine where within the distributions of host galaxy e.g. metallicities and ages each SN is found, thus providing new constraints on SN progenitor properties. This initial pilot study using MUSE opens the way for a revolution in SN environment studies where we are now able to study multiple environment SN progenitor dependencies using a single instrument and single pointing. © 2015 The Authors. | URI: | http://hdl.handle.net/10261/150282 | DOI: | 10.1093/mnras/stv2620 | Identificadores: | doi: 10.1093/mnras/stv2620 issn: 1365-2966 |
Aparece en las colecciones: | (IAA) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
IAA_2016_MNRASstv2620.pdf | 8,41 MB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
SCOPUSTM
Citations
93
checked on 16-abr-2024
WEB OF SCIENCETM
Citations
87
checked on 23-feb-2024
Page view(s)
289
checked on 19-abr-2024
Download(s)
202
checked on 19-abr-2024
Google ScholarTM
Check
Altmetric
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.